Perceptions of power-assist devices: interviews with manual wheelchair users
Bibliographic record
Abstract
PURPOSE: The study had three main objectives. (1) To investigate the perceived impact of power-assist devices (PADs) on manual wheelchair (MWC) user mobility. (2) To compare perceptions about different types of PADs. (3) To identify preferred features and design characteristics of PADs. METHODS: = 16). Data were thematically analysed using an inductive approach. RESULTS: Two main themes related to participants' perceptions about the effects of PAD use were identified: (1) "Expanding my world", which illustrated the perceived benefits of using PADs (e.g., gaining a sense of autonomy and access to new environments, maintaining physical health) and (2) "Falling short", which described challenges with PADs (e.g., safety, reliability and portability issues). Participants also identified strengths and limitations of different types of PADs that were mainly related to specific user-device and device-environment interactions as well as various functional characteristics. Moreover, participants outlined their priorities for future PAD design, including improving controllability, customizability and affordability of these devices. CONCLUSIONS: Participants' perceptions about PADs varied across different types of devices and in different contexts. However, PADs were generally perceived as enhancing the capabilities of MWCs. Our findings provide insight into the factors that can be considered when selecting a PAD and can inform the development of future PADs that are better equipped to overcome challenges that MWC users frequently encounter.Implications for RehabilitationPower-assist devices (PADs) for manual wheelchairs (MWCs) have the potential to improve the mobility, community participation and well-being of users.Some of the existing PADs have safety and reliability issues that affect their performance and limit their use by MWC users.The three types of PADs (front-mounted attachments, rear-mounted attachments, powered wheels) offer different types of assistance that can benefit users with various capabilities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".